Passive sound source classification and localization

ABSTRACT

A method for processing audible sounds using ultrasonic sensors. The method includes passively monitoring, via ultrasonic sensors, an external environment for a audible sounds. An audible sound may be detected and used to produce a sound signal. The sound signal may be filtered to determine one or more features corresponding thereto, including a class, a position, and a velocity. A priority may be assigned to the sound signal based on the sound signal to determine an appropriate response. A corresponding system and computer program product are also disclosed and claimed herein.

BACKGROUND Field of the Invention

This invention relates to sound processing for vehicles.

Background of the Invention

Ultrasonic proximity sensors are quickly becoming standard fare onmodern vehicles. These sensors are typically implemented on the frontand/or rear bumpers of vehicles to assist with vehicle parking andobstacle avoidance. Each sensor actively emits acoustic pulses and thenmeasures the return interval of each reflected signal to determinedistances to nearby objects. If objects are within a predeterminedproximity range, the sensor system alerts the driver to possible dangervia audible sounds, visible aids, and/or tactile indications.

While ultrasonic transducers have broad general application, ultrasonicproximity sensors for vehicles are typically only triggered by slowvehicle speeds (for front sensors), or by selecting a reverse gear (forrear sensors). In this manner, such sensors are automatically activatedto facilitate navigating into and out of parking spaces while avoidingnuisance warnings during driving. This mode of operation, however,effectively limits the usefulness of such sensors to parking situations,as such sensors are not equipped to inform or influence vehicle behaviorat normal driving speeds.

Many traffic conditions and obstacles encountered at normal drivingspeeds are associated with audible noises such as crashes, screeches,engine sounds, horns, sirens, railroad crossing bells, and the like.These noises may inform drivers of potentially dangerous situations,even before the particular condition or obstacle may be seen. Theseaudible warnings may be inadequate, however, to entirely preventpotentially hazardous encounters. Indeed, human drivers are notoriouslyprone to making errors of judgment, inherently limited by theirinattentiveness, distractions, and/or inability to process relevantinformation quickly and accurately.

In view of the foregoing, what are needed are systems and methods toautomatically identify and localize sounds associated with trafficconditions and obstacles encountered under normal driving conditions.Ideally, such systems and methods would utilize existing ultrasonicsensors to capture incident audible sounds to detect objects orobstacles corresponding to such sounds that may be obstructed or notdirectly visible. Such systems and methods would also and identify andlocalize multiple objects substantially simultaneously, assign apriority to each, and determine an appropriate vehicle response based onthat priority.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of the invention will be readilyunderstood, a more particular description of the invention brieflydescribed above will be rendered by reference to specific embodimentsillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered limiting of its scope, the invention will be describedand explained with additional specificity and detail through use of theaccompanying drawings, in which:

FIG. 1 is a high-level block diagram showing one example of a computingsystem in which a system and method in accordance with the invention maybe implemented;

FIG. 2 is a high level schematic diagram showing various obstacles orhazards that may be identified and localized in accordance with certainembodiments of the invention;

FIG. 3 is a graph of a typical frequency response for ultrasonic sensorsutilized in accordance with certain embodiments of the invention;

FIG. 4 is a graph of a typical noise spectrum for sounds received byultrasonic sensors in accordance with certain embodiments of theinvention;

FIG. 5 is a perspective view of a traffic situation where obstacles maybe identified and localized in accordance with certain embodiments ofthe invention;

FIG. 6 is a flow chart showing a process for identifying and localizingsounds in accordance with certain embodiments of the invention; and

FIG. 7 is a flow chart showing a process for prioritizing sounds inaccordance with embodiments of the invention.

DETAILED DESCRIPTION

Referring to FIG. 1, one example of a computing system 100 isillustrated. The computing system 100 is presented to show one exampleof an environment where a system and method in accordance with theinvention may be implemented. The computing system 100 may be embodiedas a mobile device 100 such as a smart phone or tablet, a desktopcomputer, a workstation, a server, or the like. The computing system 100is presented by way of example and is not intended to be limiting.Indeed, the systems and methods disclosed herein may be applicable to awide variety of different computing systems in addition to the computingsystem 100 shown. The systems and methods disclosed herein may alsopotentially be distributed across multiple computing systems 100.

As shown, the computing system 100 includes at least one processor 102and may include more than one processor 102. The processor 102 may beoperably connected to a memory 104. The memory 104 may include one ormore non-volatile storage devices such as hard drives 104 a, solid statedrives 104 a, CD-ROM drives 104 a, DVD-ROM drives 104 a, tape drives 104a, or the like. The memory 104 may also include non-volatile memory suchas a read-only memory 104 b (e.g., ROM, EPROM, EEPROM, and/or Flash ROM)or volatile memory such as a random access memory 104 c (RAM oroperational memory). A bus 106, or plurality of buses 106, mayinterconnect the processor 102, memory devices 104, and other devices toenable data and/or instructions to pass therebetween.

To enable communication with external systems or devices, the computingsystem 100 may include one or more ports 108. Such ports 108 may beembodied as wired ports 108 (e.g., USB ports, serial ports, Firewireports, SCSI ports, parallel ports, etc.) or wireless ports 108 (e.g.,Bluetooth, IrDA, etc.). The ports 108 may enable communication with oneor more input devices 110 (e.g., keyboards, mice, touchscreens, cameras,microphones, scanners, storage devices, etc.) and output devices 112(e.g., displays, monitors, speakers, printers, storage devices, etc.).The ports 108 may also enable communication with other computing systems100.

In certain embodiments, the computing system 100 includes a wired orwireless network adapter 114 to connect the computing system 100 to anetwork 116, such as a LAN, WAN, or the Internet. Such a network 116 mayenable the computing system 100 to connect to one or more servers 118,workstations 120, personal computers 120, mobile computing devices, orother devices. The network 116 may also enable the computing system 100to connect to another network by way of a router 122 or other device122. Such a router 122 may allow the computing system 100 to communicatewith servers, workstations, personal computers, or other devices locatedon different networks.

As previously mentioned, ultrasonic proximity sensors are commonlyimplemented on modern vehicles to facilitate parking and obstacleavoidance. Typical sensor operation involves actively emitting anacoustic pulse and measuring the return interval of the reflectedsignal, which may be automatically triggered by slow vehicle speedsand/or putting the vehicle into reverse. Such sensors are ill-equipped,however, to inform or influence vehicle behavior at normal drivingspeeds. Embodiments of the invention address this issue by utilizingultrasonic sensors to passively detect and monitor audible and inaudiblesounds during normal driving conditions. Embodiments of the inventionmay also classify and prioritize such sounds to determine an appropriatevehicle response.

As used herein, the term “vehicle” refers to any autonomous,semi-autonomous, or non-autonomous motorized vehicle, including aheavy-duty industrial or transport vehicle, bus, truck, car, cart,airplane, train, and the like. The term “ultrasonic sensor” refers toany transmitter, receiver and/or transceiver, including a microphone,configured to convert ultrasound and/or audible sound into an electricalsignal.

Referring now to FIG. 2, a system 200 for passively identifying andlocalizing audible and/or inaudible sounds in accordance with theinvention may include a vehicle 202 having an array of onboardultrasonic sensors 204. As shown, the vehicle 202 may include an arrayof ultrasonic sensors 204 disposed on its front 214 and/or rear bumpers216. In one embodiment, the vehicle 202 may include a total of twelve(12) ultrasonic sensors 204: four (4) on the front bumper 214, four (4)on the rear bumper 216, and two (2) on each side 218.

At slow speeds (such as during parking or reversing), each ultrasonicsensor 204 onboard a vehicle 202 may actively emit ultrasonicfrequencies to detect obstacles within its line of sight.Advantageously, ultrasonic sensors 204 in accordance with embodiments ofthe present invention may also passively monitor an external environmentfor incident sounds within an audible range. Passive sensing of theexternal environment by more than one ultrasonic sensor 204 in thismanner may enable detection and monitoring of more than one soundsubstantially simultaneously. These sounds may be captured by theultrasonic sensors 204 and analyzed to detect objects and obstaclescorresponding to such sounds, as discussed in more detail below.Importantly, ultrasonic sensors 204 utilized in this manner may detectobjects and obstacles that may be fully or partially obstructed, or notdirectly visible to the vehicle 202.

Other vehicular traffic, and particularly emergency vehicles andmotorcycles 212, pose some of the greatest safety threats to vehicles202 on the road. For this reason, almost all vehicles 202 are equippedwith mechanisms capable of producing distinct noises to warn othervehicles 202 of potential danger. For example, sirens on police cars206, fire engines 208, ambulances, and other emergency vehicles readilyidentify such vehicles and warn other vehicles of potential danger.Likewise, the loud engine sounds produced by a motorcycle 212 arediscernable almost immediately, while the bells of a railroad crossingbarrier 210 are widely recognized as announcing an impending train.

Despite these built-in audible warning systems, such audible noises andsounds are typically ignored by ultrasonic sensors 204 onboard a vehicle202, as such ultrasonic sensors 204 are unable to process them in auseful way. Beneficially, embodiments of the present invention mayutilize existing ultrasonic sensors 204 to capture and analyze incidentenvironmental sounds, thus enabling vehicles 202 to detect and avoidassociated obstacles and accidents.

In addition, certain embodiments of the invention may utilize ultrasonicsensors 204 in combination with other sensing modalities such as camerasensors, Lidar sensors, radar sensors, global positioning systems, andthe like, to ensure robust and reliable detection and localization ofobjects. In one embodiment, a confidence score may be generated for adetected object based on the presence or absence of corroboratingevidence received from other types of sensors, or from ultrasonicsensors 204 associated with other vehicles 202. Information that failsto meet a predetermined confidence score threshold may be ignored.

In certain embodiments, detected objects may be assigned a priorityscore for localization and/or tracking. The priority score may bespecific to an individual vehicle 202, depending on that vehicle's 202location and course of travel relative to the detected object. Forexample, the priority score may be based on a category of classification(i.e., emergency vehicles may be assigned a higher priority than othervehicles), initial position estimates (i.e., closer objects may beprioritized over objects that are farther away), current trafficconditions and policies (i.e., objects with a course of travel away fromthe vehicle 202 may be assigned a lower priority than objects with acourse of travel towards the vehicle 202), and expectation of theexistence of the object (i.e., entry barrier to a railway crossing maybe assigned a higher priority if the vehicle 202 expects to cross arailroad in the near future). In certain embodiments, the system 200 mayinterface with known train schedules, bus schedules, and the like todetermine an expectation of the existence of the object.

In some embodiments, objects having priority scores above a certainpredetermined threshold may be tracked by a vehicle 202. Thepredetermined threshold for priority scores may be pre-defined, and maychange depending on vehicle 202 configuration as well as prevailingtraffic conditions. As discussed in more detail below, the vehicle 202may track objects by monitoring their position estimates relative to thevehicle 202 over time.

Referring now to FIG. 3, embodiments of the invention may produce asound signal 306 corresponding to each sound captured by at least oneultrasonic sensor 204. Various filtering techniques, such as a fastFourier transform (“FFT”) or bandpass filters, may be applied to convertan incoming sound from its original domain to a representation in thefrequency domain 304. The resulting sound signal 306 or associatedfrequency domain values may then be passed through a pre-trainedclassification model, such as a neural network for additional analysis.

Specifically, embodiments of the invention may utilize neural networksto build predictions of different classes of sound sources, and thenassign incoming sound signals 306 to such classes. In some embodiments,the present invention may classify incoming sound signals 306 intovarious object categories based on their associated frequencies. Objectcategories may include, for example, passenger vehicles, motorcycles,police cars on active duty, fire engines on active duty, railroadcrossings, or any other such category known to those in the art.

FIG. 3 is a graph 300 illustrating typical sensitivity responses 302 ofultrasonic sensors to received frequency domain values 304. As shown,ultrasonic sensors demonstrate strong sensitivity to operating frequencyvalues 304 in a range of 50 kHz-100 kHz. However, such ultrasonicsensors also demonstrate reasonable sensitivity from 100 Hz-20 kHz,which spans most of the generally accepted range of audible frequencies(i.e., 20 Hz-20 kHz).

Upon detecting and classifying sound signals 306 received from multipleultrasonic sensors within this frequency 304 range, various types ofsignal processing algorithms may be performed to identify and localize asource of each sound signal 306 (such as an object or obstacle) inaccordance with embodiments of the invention. Signal processingalgorithms associated with beamforming, source localization, and noisereduction may be used to assign initial position estimates and velocityestimates to multiple objects substantially simultaneously. In addition,certain embodiments may track objects over time and use extrapolationtechniques, such as Doppler extrapolation, to estimate a trajectory forthe object.

In certain embodiments, a position estimate of an object may becalculated based on passively monitoring sound signals 306 captured bymultiple ultrasonic sensors 204. Beamforming techniques may be used tocombine sound signals 306 from multiple ultrasonic sensors in such a waythat sound signals 306 at particular angles experience constructiveinterference, while others experience destructive interference. In thismanner, beamforming may be used to estimate the location of the sourceof the sound signal 306 by means of optimal spatial filtering andinterference rejection. This location estimate may be refined with moresound signals 306 sampled across time.

In one embodiment, a synthetic aperture-type setup may be used inaddition to signal processing to fuse voltage signals received from thesame set of ultrasonic sensors at different points in time. This mayresult in a more robust system able to localize sound sources that emitmost of their sound signals 306 in lower frequency bands. In someembodiments, Kalman filter methods or linear quadratic estimationmethods may be applied to a series of location estimates to predictvelocities for the sound sources or objects of interest.

FIG. 4 is a graph 400 of a typical noise spectrum, demonstratingsignificantly higher noise 406 levels at lower frequencies 404. Allmaterials produce noise 406 at a power level 402 proportional to thephysical temperature of the material, and all recording devices,including ultrasonic sensors 204, have traits that make them susceptibleto noise 406. Some embodiments of the invention may performprobabilistic noise 406 reduction techniques to facilitate a highersignal to noise 406 ratio. These techniques may be particularly helpfulto clean up sound signals at lower frequencies 404, thereby producing abest estimate of the true state of the signal. Probabilistic noise 406reduction techniques may be based on a Gaussian probabilisticmathematical model, or any other probabilistic model known to those inthe art.

Probabilistic noise 406 reduction techniques may include, for example,compander-based noise reduction systems, dynamic noise limiter ordynamic noise reduction, spectral editing tools, and other suchtechniques and noise reduction software programs known to those in theart. Such techniques may be performed on an incoming sound signal 306 togenerate a “clean” sound signal.

In certain embodiments, information including the clean sound signal306, classification assigned to the sound signal 306, and direction ofthe source of the sound signal 306, may be communicated to a cloud-basedprocessor or server for further processing. The processor or server maygeocode the information and assign a time stamp to precise ego vehiclelocalization information. In some embodiments, information from onboardultrasonic sensors associated with more than one vehicle 202 may becommunicated to and processed by the processor or server. The combinedinformation from multiple detection sources may facilitate increasedaccuracy and reliability of object identification and localization.

Referring now to FIG. 5, a system 500 in accordance with the presentinvention may identify and localize objects and obstacles in a trafficsituation. As shown, heavy vehicle traffic, including a motorcycle 508,may be flowing from right to left, while a train 510 approaches an entrybarrier 512 intersecting traffic. Embodiments of the present inventionmay utilize onboard or ancillary ultrasonic sensors to detect andidentify potentially dangerous obstacles and situations, including theimpending train 510 and the motorcycle 508.

In some embodiments, this information may be shared between vehicles502, 504, 506 over a wireless network such as V2V communicationssystems, or other dedicated short-range communications (“DSRC”) systemsknown to those in the art. Information may be shared with vehicles 502,504, 506 according to their proximity to the object or obstacle, or uponuser request.

In one embodiment, for example, an array of ultrasonic sensors 204associated with the first vehicle 506 may detect the entry barrier 512.This information, in addition to information from other data sourcessuch as GPS and predetermined maps, may be passed to vehicles 502, 504that have not yet encountered the entry barrier 512, and to othervehicles in the vicinity. Using the filtered information received fromthe first vehicle 506, the other vehicles 502 and 504 may receive a morerefined estimate of the location of the entry barrier 512. Such othervehicles 502, 504 may also use the information received from the firstvehicle 506 to actively track the entry barrier 512, since it is ahigh-priority object.

In some embodiments, information from the ultrasonic sensors 204 of thefirst vehicle 506 may override information received from other datasources. For example, sensor 204 information from the first vehicle 506indicating that a train 510 is approaching may override information fromother GPS sources indicating that the railroad barrier 512 is up. Thissafety override may be critical where, as in this example, the entrybarrier 512 may have malfunctioned and later vehicles 502, 504 would notbe privy to such information but for the data from the first vehicle506.

Other vehicles in the vicinity may also receive the information butselectively ignore it by not localizing and/or tracking the entrybarrier 512. The decision to ignore such information may be based on thepriority score assigned to the entry barrier 512 for the vehicle.Indeed, the entry barrier 512 may be assigned a lower priority score forvehicles farther away from the entry barrier 512 or for vehiclestraveling in an opposite direction, such as those that have alreadypassed the entry barrier 512.

In another embodiment, vehicles 502, 504 close to the motorcycle 508 maydetect the motorcycle 508 and propagate associated information to thefirst vehicle 506 and other vehicles in the immediate vicinity. In thismanner, the first vehicle 506 may receive a more refined estimate of theposition and velocity of the motorcycle 508 based on informationgenerated by ultrasonic sensors 204 onboard vehicles 502, 504 positionedcloser to the motorcycle 508. All of the vehicles 502, 504, 506proximate the motorcycle 508 may actively track the motorcycle 508,since it is a high-priority object.

Referring now to FIG. 6, a method 600 for identifying and localizingsounds in accordance with embodiments of the invention may includeutilizing ultrasonic sensors to passively monitor 602 an externalenvironment for audible sounds. In certain embodiments, ultrasonicsensors may be coupled to or associated a vehicle and may monitor 602the external environment substantially continuously for sounds. If nosound is detected 604, the ultrasonic sensors may continue to passivelymonitor 602 the external environment. If a sound is detected 604, thesound may be converted from its original domain to produce 606 a soundsignal in a frequency domain.

The sound signal may then be filtered and classified 608 into one ormore sound source or object categories. Object categories may be definedby frequency ranges or other sound signal characteristics typicallyassociated with particular objects. As mentioned previously, objectcategories may include passenger vehicles, motorcycles, police cars onactive duty, fire engines on active duty, railroad crossings, or anyother such category known to those in the art.

The incoming sound signal may be further analyzed to determine orestimate 610 a location and/or position of the object or sound source,and to determine 612 a velocity of the object. Determining 612 avelocity of the object may be important, for example, where the object(e.g., a motorcycle) is approaching a vehicle at double the vehicle'sspeed. In the absence of a direct line of sight between the vehicle andthe motorcycle, the motorcycle may be difficult to localize and aclosing rate between the vehicle and the motorcycle may be impossible todetermine. Embodiments of the invention may overcome such difficultiesby performing a velocity calculation 612 to enable the receiving vehicleto automatically assess the situation quickly and accurately, and toautomatically initiate an appropriate response. In this manner,embodiments of the invention may the vehicle to avoid a collision orother interference with the motorcycle.

Some embodiments of the invention may prioritize 614 a sound signalbased on its corresponding classification 608, position 610, velocity612, and/or any other feature or characteristic known to those in theart. In certain embodiments, as discussed in more detail with referenceto FIG. 7 below, prioritizing 614 a sound signal may include assigning apriority score to the sound. The priority score may be compared to apredetermined threshold to determine 616 whether the sound signal isassociated with a high-priority object. If so, the object may be tracked618 until the risk of danger has passed. If not, the object may not betracked 620.

Referring now to FIG. 7, a process 700 for prioritizing sounds inaccordance with embodiments of the invention may include detecting 702 asound utilizing one or more ultrasonic sensors onboard or otherwiseassociated with a vehicle. The sound may be converted from its originaldomain to produce 704 a sound signal in a frequency domain. The soundsignal may be filtered and analyzed to determine 706 whether the soundsignal corresponds to an emergency vehicle. If yes, an associatedpriority score may be increased 712. If no, the associated priorityscore may be unchanged or decreased 714.

The sound signal may be further analyzed to determine 708 whether theobject is within a predetermined distance with respect to the vehicleand/or its associated ultrasonic sensors. If yes, the priority score forthe object may be increased 716. If not, the priority score may beunchanged or decreased 718.

Finally, the sound signal may be analyzed to determine 710 whether anencounter with the object is expected 710. For example, embodiments ofthe present invention may utilize a global positioning system and/orother sensors such as cameras, lidar, radar, and the like, to predict anencounter with an object, such as an entry barrier to a railwaycrossing. In some embodiments, sensor data may be used in combinationwith data from other sources, such as public transportation schedules oremergency vehicle projected paths based on source/origin andsink/destination. If there is an expectation of an object where, forexample, the object has been identified by GPS data or predeterminedmaps, then the priority score may be increased 720. If not, the priorityscore may be unchanged or decreased 722. A final priority score may thenbe generated 724 and used to determine an appropriate vehicle response,as discussed above.

In the above disclosure, reference has been made to the accompanyingdrawings, which form a part hereof, and in which is shown by way ofillustration specific implementations in which the disclosure may bepracticed. It is understood that other implementations may be utilizedand structural changes may be made without departing from the scope ofthe present disclosure. References in the specification to “oneembodiment,” “an embodiment,” “an example embodiment,” etc., indicatethat the embodiment described may include a particular feature,structure, or characteristic, but every embodiment may not necessarilyinclude the particular feature, structure, or characteristic. Moreover,such phrases are not necessarily referring to the same embodiment.Further, when a particular feature, structure, or characteristic isdescribed in connection with an embodiment, it is submitted that it iswithin the knowledge of one skilled in the art to affect such feature,structure, or characteristic in connection with other embodimentswhether or not explicitly described.

Implementations of the systems, devices, and methods disclosed hereinmay comprise or utilize a special purpose or general-purpose computerincluding computer hardware, such as, for example, one or moreprocessors and system memory, as discussed herein. Implementationswithin the scope of the present disclosure may also include physical andother computer-readable media for carrying or storingcomputer-executable instructions and/or data structures. Suchcomputer-readable media can be any available media that can be accessedby a general purpose or special purpose computer system.Computer-readable media that store computer-executable instructions arecomputer storage media (devices). Computer-readable media that carrycomputer-executable instructions are transmission media. Thus, by way ofexample, and not limitation, implementations of the disclosure cancomprise at least two distinctly different kinds of computer-readablemedia: computer storage media (devices) and transmission media.

Computer storage media (devices) includes RAM, ROM, EEPROM, CD-ROM,solid state drives (“SSDs”) (e.g., based on RAM), Flash memory,phase-change memory (“PCM”), other types of memory, other optical diskstorage, magnetic disk storage or other magnetic storage devices, or anyother medium which can be used to store desired program code means inthe form of computer-executable instructions or data structures andwhich can be accessed by a general purpose or special purpose computer.

An implementation of the devices, systems, and methods disclosed hereinmay communicate over a computer network. A “network” is defined as oneor more data links that enable the transport of electronic data betweencomputer systems and/or modules and/or other electronic devices. Wheninformation is transferred or provided over a network or anothercommunications connection (either hardwired, wireless, or a combinationof hardwired or wireless) to a computer, the computer properly views theconnection as a transmission medium. Transmissions media can include anetwork and/or data links, which can be used to carry desired programcode means in the form of computer-executable instructions or datastructures and which can be accessed by a general purpose or specialpurpose computer. Combinations of the above should also be includedwithin the scope of computer-readable media.

Computer-executable instructions comprise, for example, instructions anddata which, when executed at a processor, cause a general purposecomputer, special purpose computer, or special purpose processing deviceto perform a certain function or group of functions. The computerexecutable instructions may be, for example, binaries, intermediateformat instructions such as assembly language, or even source code.Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the described features or acts described above.Rather, the described features and acts are disclosed as example formsof implementing the claims.

Those skilled in the art will appreciate that the disclosure may bepracticed in network computing environments with many types of computersystem configurations, including, an in-dash vehicle computer, personalcomputers, desktop computers, laptop computers, message processors,hand-held devices, multi-processor systems, microprocessor-based orprogrammable consumer electronics, network PCs, minicomputers, mainframecomputers, mobile telephones, PDAs, tablets, pagers, routers, switches,various storage devices, and the like. The disclosure may also bepracticed in distributed system environments where local and remotecomputer systems, which are linked (either by hardwired data links,wireless data links, or by a combination of hardwired and wireless datalinks) through a network, both perform tasks. In a distributed systemenvironment, program modules may be located in both local and remotememory storage devices.

Further, where appropriate, functions described herein can be performedin one or more of: hardware, software, firmware, digital components, oranalog components. For example, one or more application specificintegrated circuits (ASICs) can be programmed to carry out one or moreof the systems and procedures described herein. Certain terms are usedthroughout the description and claims to refer to particular systemcomponents. As one skilled in the art will appreciate, components may bereferred to by different names. This document does not intend todistinguish between components that differ in name, but not function.

It should be noted that the sensor embodiments discussed above maycomprise computer hardware, software, firmware, or any combinationthereof to perform at least a portion of their functions. For example, asensor may include computer code configured to be executed in one ormore processors, and may include hardware logic/electrical circuitrycontrolled by the computer code. These example devices are providedherein purposes of illustration, and are not intended to be limiting.Embodiments of the present disclosure may be implemented in furthertypes of devices, as would be known to persons skilled in the relevantart(s).

At least some embodiments of the disclosure have been directed tocomputer program products comprising such logic (e.g., in the form ofsoftware) stored on any computer useable medium. Such software, whenexecuted in one or more data processing devices, causes a device tooperate as described herein.

While various embodiments of the present disclosure have been describedabove, it should be understood that they have been presented by way ofexample only, and not limitation. It will be apparent to persons skilledin the relevant art that various changes in form and detail can be madetherein without departing from the spirit and scope of the disclosure.Thus, the breadth and scope of the present disclosure should not belimited by any of the above-described exemplary embodiments, but shouldbe defined only in accordance with the following claims and theirequivalents. The foregoing description has been presented for thepurposes of illustration and description. It is not intended to beexhaustive or to limit the disclosure to the precise form disclosed.Many modifications and variations are possible in light of the aboveteaching. Further, it should be noted that any or all of theaforementioned alternate implementations may be used in any combinationdesired to form additional hybrid implementations of the disclosure.

The invention claimed is:
 1. A method comprising: passively monitoring,with at least one ultrasonic sensor, an outdoor environment for audiblesounds; converting, by the at least one ultrasonic sensor, an audiblesound into an electrical signal; processing, by a neural network trainedto perform classification with respect to a plurality of classes, theelectrical signal in order to classify a source of the audible sound aspertaining to a first class of the plurality of classes; analyzing, by acomputer system, the electrical signal to estimate at least one of arelative position and a relative velocity corresponding to the source;and assigning, by the computer system, a priority to the source based onat least one of the first class, the relative position, and the relativevelocity.
 2. The method of claim 1, wherein the at least one ultrasonicsensor is carried onboard a first vehicle.
 3. The method of claim 2,further comprising tracking the source when the priority is above athreshold and not tracking the source when the priority is below thethreshold.
 4. The method of claim 3, wherein tracking comprisesmonitoring the relative position of the source with respect to the firstvehicle.
 5. The method of claim 1, wherein assigning the priority to thesource further comprises assigning the priority based on at least one ofcurrent traffic conditions, behavior policies, and expectations ofobjects.
 6. The method of claim 5, wherein the priority assigned by thecomputer system to the source changes over time.
 7. The method of claim2, further comprising communicating at least one of the first class, therelative position, and the relative velocity to a second vehicle.
 8. Themethod of claim 7, wherein the communicating comprises sending the atleast one of the first class, the relative position, and the relativevelocity directly from the first vehicle to the second vehicle viawireless communication.
 9. The method of claim 1, further comprisinggenerating a confidence score for at least one of the relative positionand the relative velocity.
 10. The method of claim 9, wherein theconfidence score is based at least partially on information receivedfrom at least one of another sensor type and a remotely-locatedultrasonic sensor.
 11. A system comprising: an ultrasonic sensor; atleast one processor; and at least one memory device operably connectedto the at least one processor and storing instructions for execution bythe at least one processor, the instructions causing the at least oneprocessor to: receive an electrical signal from the ultrasonic sensor,wherein the electrical signal is generated by the ultrasonic sensor inresponse to the ultrasonic sensor receiving an audible sound emanatingfrom a source, process, using a neural network trained to performclassification with respect to a plurality of classes, the electricalsignal in order to classify the source as pertaining to a first class ofthe plurality of classes, analyze the electrical signal to estimate atleast one of a relative position and a relative velocity correspondingto the source, and assign a priority to the source based on at least oneof the first class, the relative position, and the relative velocity.12. The system of claim 11, wherein the at least one ultrasonic sensoris carried onboard a first vehicle.
 13. The system of claim 11, whereinthe instructions further cause the at least one processor to track thesource when the priority is above a threshold and not track the sourcewhen the priority is below the threshold.
 14. The system of claim 13,wherein to track the source is to monitor the relative position of thesource with respect to the first vehicle.
 15. The system of claim 11,wherein to assign the priority to the source is to assign the prioritybased on at least one of current traffic conditions, behavior policies,and expectations of objects.
 16. The system of claim 15, wherein thepriority assigned to the source changes over time.
 17. The system ofclaim 12, wherein the instructions further cause the processor tocommunicate at least one of the first class, the relative position, andthe relative velocity to a second vehicle.
 18. The system of claim 11,wherein to communicate the at least one of the first class, the relativeposition, and the relative velocity to the second vehicle is tocommunicate the at least one of the first class, the relative position,and the relative velocity directly to the second vehicle via wirelesscommunication.